class_docstr: A structured environment which returns random actions
code: def __init__(self, maze_env: MazeEnv):
      Wrapper.__init__(self, maze_env)
  
      # initialize action space
      self._action_spaces_dict = {
          0: filter_spaces_start_with(
              maze_env.action_space.spaces, "action_0"
          ),
          1: filter_spaces_start_with(
              maze_env.action_space.spaces, "action_1"
          ),
      }
      self._observation_spaces_dict = {
          0: filter_spaces_start_with(
              maze_env.observation_space.spaces, "observation_0"
          ),
          1: filter_spaces_start_with(
              maze_env.observation_space.spaces, "observation_1"
          ),
      }
  
      StructuredEnv.__init__(self)
      self._num_sub_steps = len(self._action_spaces_dict)
      self._sub_step_index = 0
      self.maze_env = maze_env
  
      self.last_obs = None
  
imports: from typing import Any, Dict, Union, Tuple, Callable, Optional
  import gym
  import numpy
  from maze.core.env.maze_env import MazeEnv
  from maze.core.env.structured_env import StructuredEnv, StepKeyType, ActorID
  from maze.core.env.structured_env_spaces_mixin import StructuredEnvSpacesMixin
  from maze.core.wrappers.wrapper import Wrapper
label_desc: Use image node_id 1 to create a new DummyStructuredEnvironment object from inherited base classes: Wrapper, StructuredEnv, StructuredEnvSpacesMixin with example: obj = DummyStructuredEnvironment(maze_env)